The University of Southampton
University of Southampton Institutional Repository

Flipping forests: estimating future carbon sequestration of the boreal forest using remotely sensed data

Flipping forests: estimating future carbon sequestration of the boreal forest using remotely sensed data
Flipping forests: estimating future carbon sequestration of the boreal forest using remotely sensed data
To reduce uncertainty in national and global carbon budgets, carbon sequestration can be estimated for large areas of land by driving an aspatial ecosystem simulation model (ESM) spatially, with remotely sensed biophysical data. This letter investigates the impact of future climate change on the boreal forest carbon budget by driving the FOREST-BGC (-Bio-Geochemical Cycling) ESM (under three different carbon dioxide (CO2) emission scenarios) using remotely sensed (NOAA AVHRR) estimates of leaf area index (LAI) as part of the Boreal Ecosystem Atmosphere Study (BOREAS).We demonstrate that boreal forests will continue to provide a substantial 'brake' on the rate of increase in atmospheric CO2, provided anthropogenic emissions reduce dramatically to within the limits of the 'Kyoto Protocol'. However, if anthropogenic emissions follow the unmitigated scenario (i.e. 'business as usual'), carbon sequestration will increase to a maximum by around 2050 but thereafter collapse, resulting in a disappearance of the boreal carbon sink by around 2080. An ESM and remotely sensed data was a viable predictive tool for the study of carbon sequestration over land and has potential as an aid for policy and management decisions.
0143-1161
835-842
Wicks, T.E.
a43a6197-48b3-42aa-b168-20a1584ade9b
Curran, P.J.
3f5c1422-c154-4533-9c84-f2afb77df2de
Wicks, T.E.
a43a6197-48b3-42aa-b168-20a1584ade9b
Curran, P.J.
3f5c1422-c154-4533-9c84-f2afb77df2de

Wicks, T.E. and Curran, P.J. (2003) Flipping forests: estimating future carbon sequestration of the boreal forest using remotely sensed data. International Journal of Remote Sensing, 24 (4), 835-842. (doi:10.1080/014311603762876078).

Record type: Article

Abstract

To reduce uncertainty in national and global carbon budgets, carbon sequestration can be estimated for large areas of land by driving an aspatial ecosystem simulation model (ESM) spatially, with remotely sensed biophysical data. This letter investigates the impact of future climate change on the boreal forest carbon budget by driving the FOREST-BGC (-Bio-Geochemical Cycling) ESM (under three different carbon dioxide (CO2) emission scenarios) using remotely sensed (NOAA AVHRR) estimates of leaf area index (LAI) as part of the Boreal Ecosystem Atmosphere Study (BOREAS).We demonstrate that boreal forests will continue to provide a substantial 'brake' on the rate of increase in atmospheric CO2, provided anthropogenic emissions reduce dramatically to within the limits of the 'Kyoto Protocol'. However, if anthropogenic emissions follow the unmitigated scenario (i.e. 'business as usual'), carbon sequestration will increase to a maximum by around 2050 but thereafter collapse, resulting in a disappearance of the boreal carbon sink by around 2080. An ESM and remotely sensed data was a viable predictive tool for the study of carbon sequestration over land and has potential as an aid for policy and management decisions.

This record has no associated files available for download.

More information

Published date: 2003

Identifiers

Local EPrints ID: 14798
URI: http://eprints.soton.ac.uk/id/eprint/14798
ISSN: 0143-1161
PURE UUID: fbe89b67-b0f9-4342-9d85-4e5ccbf5420d

Catalogue record

Date deposited: 01 Mar 2005
Last modified: 15 Mar 2024 05:31

Export record

Altmetrics

Contributors

Author: T.E. Wicks
Author: P.J. Curran

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×